The development of cardiovascular disease starts early in life; however, data are sparse regarding the long- term patterns of cardiovascular risk factor levels starting in early adulthood and the occurrence of CVD later in life. Given the interest in CV health across the lifespan, pooling existing data from multiple cohorts to create a synthetic cohort enabling the study of CV health across the lifespan may provide critical insights. This approach is intuitively appealing, but methodologically complex. We propose to use data from The Lifetime Risk Pooling Project (including 21 studies, n=150,000) to create a synthetic cohort which can provide insight on how long-term patterns in cardiovascular health are associated with the incidence of CVD. We will utilize sophisticated statistical methods including multilevel multiple imputation to leverage the existing data to create a synthetic cohort Using this synthetic cohort we will be able to determine long-term trajectories, starting at age 18 in CV risk factors including blood pressure, body weight, lipids and glucose and their time-varying impact on the incidence of CVD. This study will provide a validated method by which multiple cohorts can be pooled together to create a synthetic cohort capable of examining the long-term trajectories in CV risk factor levels and their time-varying association with CVD events. While the development of the missing longitudinal data is methodologically complex, once created more traditional analytic methods can be used to examine a broad range of questions.